Boron microlocalization in oral mucosal tissue: implications for boron neutron capture therapy

Clinical studies of the treatment of glioma and cutaneous melanoma using boron neutron capture therapy (BNCT) are currently taking place in the USA, Europe and Japan. New BNCT clinical facilities are under construction in Finland, Sweden, England and California. The observation of transient acute effects in the oral mucosa of a number of glioma patients involved in the American clinical trials, suggests that radiation damage of the oral mucosa could be a potential complication in future BNCT clinical protocols, involving higher doses and larger irradiation field sizes. The present investigation is the first to use a high resolution surface analytical technique to relate the microdistribution of boron-10 (10B) in the oral mucosa to the biological effectiveness of the 10B(n,α)7Li neutron capture reaction in this tissue. The two boron delivery agents used clinically in Europe/Japan and the USA, borocaptate sodium (BSH) and p-boronophenylalanine (BPA), respectively, were evaluated using a rat ventral tongue model. 10B concentrations in various regions of the tongue mucosa were estimated using ion microscopy. In the epithelium, levels of 10B were appreciably lower after the administration of BSH than was the case after BPA. The epithelium:blood 10B partition ratios were 0.2:1 and 1:1 for BSH and BPA respectively. The 10B content of the lamina propria was higher than that measured in the epithelium for both BSH and BPA. The difference was most marked for BSH, where 10B levels were a factor of six higher in the lamina propria than in the epithelium. The concentration of 10B was also measured in blood vessel walls where relatively low levels of accumulation of BSH, as compared with BPA, was demonstrated in blood vessel endothelial cells and muscle. Vessel wall:blood 10B partition ratios were 0.3:1 and 0.9:1 for BSH and BPA respectively. Evaluation of tongue mucosal response (ulceration) to BNC irradiation indicated a considerably reduced radiation sensitivity using BSH as the boron delivery agent relative to BPA. The compound biological effectiveness (CBE) factor for BSH was estimated at 0.29 ± 0.02. This compares with a previously published CBE factor for BPA of 4.87 ± 0.16. It was concluded that variations in the microdistribution profile of 10B, using the two boron delivery agents, had a significant effect on the response of oral mucosa to BNC irradiation. From a clinical perspective, based on the findings of the present study, it is probable that potential radiation-induced oral mucositis will be restricted to BNCT protocols involving BPA. However, a thorough high resolution analysis of 10B microdistribution in human oral mucosal tissue, using a technique such as ion microscopy, is a prerequisite for the use of experimentally derived CBE factors in clinical BNCT. © 2000 Cancer Research Campaig

Lexical access to large vocabularies for speech recognition

A large vocabulary isolated word recognition system based on the hypothesize-and-test paradigm is described. The system has been, however, devised as a word hypothesizer for a continuous speech understanding system able to answer to queries put to a geographical database. Word preselection is achieved by segmenting and classifying the input signal in terms of broad phonetic classes. Due to low redundancy of this phonetic code for lexical access, to achieve high performance, a lattice of phonetic segments is generated, rather than a single sequence of hypotheses. It can be organized as a graph, and word hypothesization is obtained by matching this graph against the models of all vocabulary words. A word model is itself a phonetic representation made in terms of a graph accounting for deletion, substitution, and insertion errors. A modified Dynamic Programming (DP) matching procedure gives an efficient solution to this graph-to-graph matching problem. Hidden Markov Models (HMM's) of subword units are used as a more detailed knowledge in the verification step. The word candidates generated by the previous step are represented as sequences of diphone-like subword units, and the Viterbi algorithm is used for evaluating their likelihood. To reduce storage and computational costs, lexical knowledge is organized in a tree structure where the initial common subsequences of word descriptions are shared, and a beam-search strategy carries on the most promising paths only. The results show that a complexity reduction of about 73 percent can be achieved by using the two pass approach with respect to the direct approach, while the recognition accuracy remains comparable